Tanya Berger-Wolf is weaving biology and machine learning into a new field of science for wildlife conservation. By Ross Bishoff Her life’s work had been leading to this moment, this decision. Still, it was a hard decision. The timing was rocky. After years of leading wildlife conservation efforts...
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The Imageomics Institute is hiring two new full-time positions to provide technical support for key NSF grant and sub-grant activities. The Research Data Manager and Technology Coordinator will provide broad technical and software support for data products and related key NSF grant and sub-grant...
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The work of researchers from the Imageomics Institute were featured during the IEEE 2022 Conference on Computer Vision and Pattern Recognition (CVPR) held between June 19 - 24. Recent results from Imageomics projects were shared through three juried conference proceedings that are available via open...
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illustration of bird guide laid over background of countless photographs

Images as the source of information about life

Biologists must analyze traits in order to understand the significance of patterns in the two billion-year evolutionary history of life and to predict future effects of environmental change or genetic manipulation. Images are by far the most abundant source of documentation of life on the planet—but traits of organisms cannot be readily extracted from them.

The question: How do we take hundreds of thousands of images and use them to answer fundamental biological questions about ecology and evolution? At the very least, how do we extract traits, such as the example of a bird guide?

The answer: We make traits computable. Biology meets machine learning and vice versa.

Introducing imageomics (NSF OAC-2118240)

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